Abstract
About 80% of all cancers are diagnosed in the elderly and up to 75% of cancers are associated with behavioral factors. An approach to estimate the contribution of various measurable factors, including behavior/lifestyle, to cancer risk in the US elderly population is presented. The nationally representative National Long-Term Care Survey (NLTCS) data were used for measuring functional status and behavioral factors in the US elderly population (65+), and Medicare Claims files linked to each person from the NLTCS were used for estimating cancer incidence. The associations (i.e., relative risks) of selected factors with risks of breast, prostate, lung and colon cancers were evaluated and discussed. Behavioral risk factors significantly affected cancer risks in the US elderly. The most influential of potentially preventable risk factors can be detected with this approach using NLTCS-Medicare linked dataset and for further deeper analyses employing other datasets with detailed risk factors description.
Highlights
The nationally representative National Long-Term Care Survey (NLTCS) data were used for measuring functional status and behavioral factors in the US elderly population (65+), and Medicare Claims files linked to each person from the NLTCS were used for estimating cancer incidence
All three methods took into account the fact that age is the main and well-documented cancer risk factor
Using the three approaches discussed above, we calculated the age-adjusted associations between behavioral factors and the risk of four most common cancers and selected the most significant lifestyle variables associated with increased cancer risk
Summary
About 80% of all cancers are diagnosed at ages above 65 years, and up to 75% of cancers are thought to be associated with behavioral factors—if modified, they could significantly reduce cancer burden [1]. The availability of large datasets with more detailed information provides a new prospective in studying the role of behavioral factors in the cancer risk both for each factor alone and by taking into account risk factor interactions. The most influential is study design biases (e.g., selection bias): for example, due to the fact that information on behavioral factors is usually collected by interviewing the patients with diagnosed cancers causing the bias of the estimates. The prospective cohort studies can avoid most of methodological biases; they are typically expensive, especially, when detailed questionnaires are required
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
